Pattern recognition as one field of machine learning means a study that recognizes regularities of a pattern and data. A pattern recognition technology includes a supervised learning method and an unsupervised learning method. The supervised learning method means a method in which an algorithm learns the pattern recognition by using data (referred to as “training” data) in which a result of the pattern recognition is already determined. Herein, respective training data may be called labeled data. The unsupervised learning method means a method in which the algorithm discovers a pattern which is not previously known without the labeled data.
A neural network may be used in order to implement the pattern recognition technology. The neutral network is constituted by two or more nodes and links linking the nodes. Weights may be set in the respective links and the weights granted to the links are variable. The weights assigned to the links may be modified to be suitable for performing the pattern recognition intended by the neural network.
U.S. Pat. No. 7,698,239 illustrates one example of the neural network.